{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tushare as ts\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import warnings\n",
    "import sys\n",
    "import datetime\n",
    "import talib\n",
    "import numpy as np\n",
    "sys.path.append(\"..\")\n",
    "\n",
    "from imp import reload\n",
    "\n",
    "# reload(common)\n",
    "# reload(common.analysis_helper)\n",
    "\n",
    "from common.config_helper import config_helper\n",
    "from common.analysis_helper import analysis_helper\n",
    "#import common.date_helper\n",
    "#reload(common.date_helper)\n",
    "\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "config = config_helper()\n",
    "start_date = \"20200101\"\n",
    "end_date = \"20201231\"\n",
    "pro = ts.pro_api(config.tushare_token)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>trade_date</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>change</th>\n",
       "      <th>pct_chg</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>600685.SH</td>\n",
       "      <td>20201231</td>\n",
       "      <td>24.00</td>\n",
       "      <td>26.58</td>\n",
       "      <td>23.91</td>\n",
       "      <td>26.58</td>\n",
       "      <td>24.16</td>\n",
       "      <td>2.42</td>\n",
       "      <td>10.0166</td>\n",
       "      <td>626615.43</td>\n",
       "      <td>1633441.950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>600685.SH</td>\n",
       "      <td>20201230</td>\n",
       "      <td>23.90</td>\n",
       "      <td>24.44</td>\n",
       "      <td>23.56</td>\n",
       "      <td>24.16</td>\n",
       "      <td>24.16</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>112889.17</td>\n",
       "      <td>270370.061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>600685.SH</td>\n",
       "      <td>20201229</td>\n",
       "      <td>24.38</td>\n",
       "      <td>25.31</td>\n",
       "      <td>24.10</td>\n",
       "      <td>24.16</td>\n",
       "      <td>24.36</td>\n",
       "      <td>-0.20</td>\n",
       "      <td>-0.8210</td>\n",
       "      <td>105203.22</td>\n",
       "      <td>260162.007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>600685.SH</td>\n",
       "      <td>20201228</td>\n",
       "      <td>24.99</td>\n",
       "      <td>25.05</td>\n",
       "      <td>24.20</td>\n",
       "      <td>24.36</td>\n",
       "      <td>25.25</td>\n",
       "      <td>-0.89</td>\n",
       "      <td>-3.5248</td>\n",
       "      <td>132036.21</td>\n",
       "      <td>323597.170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>600685.SH</td>\n",
       "      <td>20201225</td>\n",
       "      <td>25.50</td>\n",
       "      <td>25.50</td>\n",
       "      <td>24.63</td>\n",
       "      <td>25.25</td>\n",
       "      <td>25.82</td>\n",
       "      <td>-0.57</td>\n",
       "      <td>-2.2076</td>\n",
       "      <td>168412.72</td>\n",
       "      <td>421060.629</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     ts_code trade_date   open   high    low  close  pre_close  change  \\\n",
       "0  600685.SH   20201231  24.00  26.58  23.91  26.58      24.16    2.42   \n",
       "1  600685.SH   20201230  23.90  24.44  23.56  24.16      24.16    0.00   \n",
       "2  600685.SH   20201229  24.38  25.31  24.10  24.16      24.36   -0.20   \n",
       "3  600685.SH   20201228  24.99  25.05  24.20  24.36      25.25   -0.89   \n",
       "4  600685.SH   20201225  25.50  25.50  24.63  25.25      25.82   -0.57   \n",
       "\n",
       "   pct_chg        vol       amount  \n",
       "0  10.0166  626615.43  1633441.950  \n",
       "1   0.0000  112889.17   270370.061  \n",
       "2  -0.8210  105203.22   260162.007  \n",
       "3  -3.5248  132036.21   323597.170  \n",
       "4  -2.2076  168412.72   421060.629  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_zcfw = pro.daily(ts_code=\"600685.SH\", start_date = start_date, end_date = end_date)\n",
    "df_zcfw.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ts_code</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>pre_close</th>\n",
       "      <th>change</th>\n",
       "      <th>pct_chg</th>\n",
       "      <th>vol</th>\n",
       "      <th>amount</th>\n",
       "      <th>rtn</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trade_date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-12-31</th>\n",
       "      <td>600685.SH</td>\n",
       "      <td>24.00</td>\n",
       "      <td>26.58</td>\n",
       "      <td>23.91</td>\n",
       "      <td>26.58</td>\n",
       "      <td>24.16</td>\n",
       "      <td>2.42</td>\n",
       "      <td>10.0166</td>\n",
       "      <td>626615.43</td>\n",
       "      <td>1633441.950</td>\n",
       "      <td>0.095461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-30</th>\n",
       "      <td>600685.SH</td>\n",
       "      <td>23.90</td>\n",
       "      <td>24.44</td>\n",
       "      <td>23.56</td>\n",
       "      <td>24.16</td>\n",
       "      <td>24.16</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>112889.17</td>\n",
       "      <td>270370.061</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-29</th>\n",
       "      <td>600685.SH</td>\n",
       "      <td>24.38</td>\n",
       "      <td>25.31</td>\n",
       "      <td>24.10</td>\n",
       "      <td>24.16</td>\n",
       "      <td>24.36</td>\n",
       "      <td>-0.20</td>\n",
       "      <td>-0.8210</td>\n",
       "      <td>105203.22</td>\n",
       "      <td>260162.007</td>\n",
       "      <td>-0.008244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-28</th>\n",
       "      <td>600685.SH</td>\n",
       "      <td>24.99</td>\n",
       "      <td>25.05</td>\n",
       "      <td>24.20</td>\n",
       "      <td>24.36</td>\n",
       "      <td>25.25</td>\n",
       "      <td>-0.89</td>\n",
       "      <td>-3.5248</td>\n",
       "      <td>132036.21</td>\n",
       "      <td>323597.170</td>\n",
       "      <td>-0.035884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-25</th>\n",
       "      <td>600685.SH</td>\n",
       "      <td>25.50</td>\n",
       "      <td>25.50</td>\n",
       "      <td>24.63</td>\n",
       "      <td>25.25</td>\n",
       "      <td>25.82</td>\n",
       "      <td>-0.57</td>\n",
       "      <td>-2.2076</td>\n",
       "      <td>168412.72</td>\n",
       "      <td>421060.629</td>\n",
       "      <td>-0.022323</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              ts_code   open   high    low  close  pre_close  change  pct_chg  \\\n",
       "trade_date                                                                      \n",
       "2020-12-31  600685.SH  24.00  26.58  23.91  26.58      24.16    2.42  10.0166   \n",
       "2020-12-30  600685.SH  23.90  24.44  23.56  24.16      24.16    0.00   0.0000   \n",
       "2020-12-29  600685.SH  24.38  25.31  24.10  24.16      24.36   -0.20  -0.8210   \n",
       "2020-12-28  600685.SH  24.99  25.05  24.20  24.36      25.25   -0.89  -3.5248   \n",
       "2020-12-25  600685.SH  25.50  25.50  24.63  25.25      25.82   -0.57  -2.2076   \n",
       "\n",
       "                  vol       amount       rtn  \n",
       "trade_date                                    \n",
       "2020-12-31  626615.43  1633441.950  0.095461  \n",
       "2020-12-30  112889.17   270370.061  0.000000  \n",
       "2020-12-29  105203.22   260162.007 -0.008244  \n",
       "2020-12-28  132036.21   323597.170 -0.035884  \n",
       "2020-12-25  168412.72   421060.629 -0.022323  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "a_helper = analysis_helper(df_zcfw)\n",
    "a_helper.init_df()\n",
    "a_helper.df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "trade_date\n",
       "2020-12-31    2.42\n",
       "2020-12-30    0.28\n",
       "2020-12-29    0.95\n",
       "2020-12-28   -0.20\n",
       "2020-12-25   -0.32\n",
       "              ... \n",
       "2020-01-08    1.52\n",
       "2020-01-07    0.15\n",
       "2020-01-06    0.43\n",
       "2020-01-03    0.26\n",
       "2020-01-02    0.23\n",
       "Length: 243, dtype: float64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a_helper.df.hprechange =  a_helper.df.high - a_helper.df.pre_close\n",
    "a_helper.df.hprechange"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bigger</th>\n",
       "      <th>zero</th>\n",
       "      <th>small</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>high</th>\n",
       "      <td>193</td>\n",
       "      <td>5</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>open</th>\n",
       "      <td>97</td>\n",
       "      <td>18</td>\n",
       "      <td>128</td>\n",
       "    </tr>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      bigger  zero  small\n",
       "high     193     5     45\n",
       "open      97    18    128"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_res = a_helper.GetAnalyInfo()\n",
    "df_res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f4f61d42940>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "a_helper.df.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f4f60f08908>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "a_helper.df.rtn.plot()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0    243\n",
       "dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a_helper.df.close.plot()\n",
    "sma5 = talib.SMA(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "rtn = a_helper.df.rtn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.09546068,  0.        , -0.00824407, -0.03588371, -0.02232323,\n",
       "        0.05451917,  0.0375044 , -0.03135053,  0.02079077, -0.0046112 ,\n",
       "       -0.02396809, -0.02101087,  0.00039992, -0.01192857,  0.00753822,\n",
       "       -0.02283564,  0.01529742, -0.00944145, -0.00507714,  0.00312134,\n",
       "       -0.00700937, -0.01540269,  0.00613264, -0.01070756,  0.00038045,\n",
       "        0.03405902, -0.03101024, -0.02040116, -0.01411089, -0.00807937,\n",
       "        0.04297317,  0.00728112, -0.03328598,  0.00410066,  0.01581358,\n",
       "        0.00151918, -0.01508893, -0.01744338,  0.03443454, -0.02482264,\n",
       "       -0.00813915,  0.03869027,  0.05268514, -0.04576736, -0.03672569,\n",
       "       -0.01329414, -0.01239535,  0.02680535, -0.01514341,  0.00330457,\n",
       "       -0.01242706, -0.03778069, -0.00349162, -0.00452096, -0.00415513,\n",
       "       -0.02390008, -0.01772325, -0.0138251 ,  0.01847628,  0.01037666,\n",
       "        0.02797862,  0.0445776 , -0.0404167 ,  0.06384384, -0.03314818,\n",
       "       -0.01564198, -0.04111825,  0.04855323,  0.02555475,  0.00109429,\n",
       "       -0.0202319 ,  0.0093425 , -0.01469297,  0.01505405, -0.0232029 ,\n",
       "       -0.03501831, -0.00915726, -0.047149  , -0.00289436, -0.02128754,\n",
       "       -0.04937382,  0.01416326, -0.0015163 ,  0.03202244,  0.00533335,\n",
       "       -0.01777132, -0.04057475,  0.00714714,  0.01232913, -0.04061622,\n",
       "       -0.04543655, -0.00553711,  0.03941952,  0.01271693, -0.00377414,\n",
       "       -0.06966878,  0.00569184, -0.01590973, -0.03056086,  0.06568084,\n",
       "        0.00834729, -0.10494132,  0.05480824, -0.04113021, -0.03557489,\n",
       "       -0.0007381 ,  0.00147674, -0.06669137,  0.05688737,  0.09538335,\n",
       "        0.09536384, -0.0129034 ,  0.09531018, -0.04848487,  0.03195557,\n",
       "        0.03431473,  0.09544069,  0.0952025 ,  0.09519175,  0.09513651,\n",
       "        0.09511918,  0.00157687,  0.07536316,  0.01485742,  0.02802285,\n",
       "       -0.00118343,  0.00533651,  0.00297708, -0.01773096, -0.01972222,\n",
       "        0.02441982, -0.01170288, -0.01672955,  0.04325631,  0.00719428,\n",
       "       -0.03139138,  0.01350182, -0.00295073,  0.00947313,  0.00536834,\n",
       "       -0.00893129,  0.0053492 , -0.03972485, -0.01365209,  0.01079249,\n",
       "        0.02019105, -0.00174673,  0.03733767, -0.02739897,  0.01182047,\n",
       "       -0.0344761 , -0.00686895,  0.00228441, -0.03814259, -0.01257878,\n",
       "        0.09156719,  0.03577223,  0.0250013 , -0.01632177,  0.00249377,\n",
       "        0.0304206 , -0.0057748 ,  0.00964328,  0.03617626,  0.09551114,\n",
       "        0.01335331, -0.05024719, -0.06662264, -0.01123236,  0.02461049,\n",
       "       -0.00671143,  0.02027096,  0.0158242 , -0.01718846,  0.00752655,\n",
       "        0.01174452, -0.00069469,  0.00557105, -0.03566908, -0.01072396,\n",
       "        0.03597266,  0.03875089, -0.02343025,  0.04889543, -0.03831332,\n",
       "        0.03536998,  0.09553063,  0.01056491, -0.00488999,  0.01804807,\n",
       "        0.01249496, -0.02810102,  0.01560607,  0.00581156, -0.02385963,\n",
       "       -0.02805795, -0.03342713, -0.00761618, -0.02768602,  0.00815121,\n",
       "        0.01272949, -0.03625998, -0.01012301,  0.02402737, -0.00294334,\n",
       "        0.01629666,  0.02878987, -0.06473066, -0.03469375,  0.03757975,\n",
       "       -0.01861185, -0.00988011,  0.00988011,  0.0099787 , -0.00784877,\n",
       "        0.02519025,  0.05467479, -0.00384173, -0.01295256,  0.0030326 ,\n",
       "        0.00991996,  0.01701511,  0.003125  ,  0.0133913 ,  0.01840788,\n",
       "       -0.05881742, -0.10543667, -0.02169577, -0.01067388, -0.02231064,\n",
       "        0.01043715, -0.01432316,  0.00518472, -0.01739174,  0.00383878,\n",
       "       -0.01083849, -0.01134943, -0.04834224,  0.09519071,  0.0052701 ,\n",
       "        0.00463424,  0.0113448 ,  0.01011813])"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rtn = np.array(rtn)\n",
    "rtn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f4f49d14cc0>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0.12.2'"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sm.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(fit_ar.roots)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
